Applied Data Science Capstone by IBM/Coursera
Author: Mariusz Machczyński
The world, where we are living, seems to be very big and many places are known to us by names or photos only. Of course, during vacations we have posibility to travel across and admire them for a while. Unfortunately, there is nothing for free, so huge part of our lifes we spend at work.
Nowadays multinational companies are very common, and their current and new employees have possibility to choose preferrable locations among of available ones. Of course, there are a lot of the luckiest employees, who may work remotely from their homes, but number of jobs which can be done in that way is rather limited. In many cases we must relocate to another place, very often to another city or even another country. Relocation to another place is stressful and may influence on employees' efficiency at work, so it is not the issue for employees themselves only, but for employers too. When a company have a few sites where an employee can work, then by providing possibility of choice to the employee, the company may reduce relocation stress and be more satisfied with the employee's work results. Of course, such situation takes place more often for new employees than for old ones, but old ones very often can do it themselves using internal jobs market, which is very common in that kind of companies.
Usually we feel comfortable when we are living in the environment known to us. When we must change it due to relocation then our stress will be smaller when new one is similar to the old one. But how to pick up the right one among few proposed? That problem can be solved by data science, which can show us similarities and dissimilarities between different places, and allows us to make better choice.
Let us assume, that there is a company, hereinafter named as Company, which has its production sites in three different cities: New York, Chicago and Dallas. Company is recruiting a new employee for a job, which can be done at any of its sites, and would like to provide to the employee the most convenient living environment, because the employee's skills are absolutely needed for Company. The employee is living in city Toronto and relocation to new place is required.
Due to the fact, that it is crucial to Company to employ the best of the best, Company decides to increase attractiveness of its job offer not only by giving free choice of three different places to live but also by providing them ordered by similarity to the place, where the employee currently lives. So, it is natural, that Company asked a data scientist to create the relevant comparison, which may convince the hesitating employee.
Data needed to compare those four different cities will be a combination of:
The comparison will be done at three different levels:
Collected data will be processed to find out similarities at all levels by segmentation and clustering neighborhoods of all cities. k-means clustering algorithm will be used for clustering neighborhoods. To avoid potential data difference between venues explored in all neighborhoods of a city, all boroughs of the city and the city itself, venues will be retrieved for neighborhoods only and they will be concatenated for boroughs and cities levels.
Cites and boroughs similarity will be obtained by distance calculation between their features, which are cluster labels obtained for neighborhoods, then ordered into the list.
The result of the comparison at cities level will give the employee easy choice of the most similar city to that, where the employee currently lives. The result of comparison at neighborhoods and boroughs levels will guide the employee through neighbourhoods and boroughs of chosen city.
Let us scrape data from various sources and build list of neighborhoods for each city.
| State | City | Borough | Neighborhood | |
|---|---|---|---|---|
| 0 | Ontario | Toronto | North York | Parkwoods |
| 1 | Ontario | Toronto | North York | Victoria Village |
| 2 | Ontario | Toronto | Downtown Toronto | Harbourfront |
| 3 | Ontario | Toronto | North York | Lawrence Heights |
| 4 | Ontario | Toronto | North York | Lawrence Manor |
| State | City | Borough | Neighborhood | |
|---|---|---|---|---|
| 0 | New York | New York | Bronx | Melrose |
| 1 | New York | New York | Bronx | Mott Haven |
| 2 | New York | New York | Bronx | Port Morris |
| 3 | New York | New York | Bronx | Hunts Point |
| 4 | New York | New York | Bronx | Longwood |
| State | City | Borough | Neighborhood | |
|---|---|---|---|---|
| 0 | Illinois | Chicago | Far North Side | Loyola |
| 1 | Illinois | Chicago | Far North Side | Rogers Park |
| 2 | Illinois | Chicago | Far North Side | Nortown |
| 3 | Illinois | Chicago | Far North Side | Peterson Park |
| 4 | Illinois | Chicago | Far North Side | Rosehill |
| State | City | Borough | Neighborhood | |
|---|---|---|---|---|
| 0 | Texas | Dallas | Downtown Dallas | Baylor District |
| 1 | Texas | Dallas | Downtown Dallas | The Cedars |
| 2 | Texas | Dallas | Downtown Dallas | Civic Center District |
| 3 | Texas | Dallas | Downtown Dallas | Dallas Arts District |
| 4 | Texas | Dallas | Downtown Dallas | Dallas Farmers Market |
Let us retrieve geolocation data for each city's neighbourhood and visualize them on maps.
Let us explore each city's neighborhood and find out venues there.
| State | City | Borough | Neighborhood | Neighborhood Latitude | Neighborhood Longitude | Venue | Venue Latitude | Venue Longitude | Venue Category | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ontario | Toronto | North York | Parkwoods | 43.752777 | -79.326440 | Brookbanks Park | 43.751976 | -79.332140 | Park |
| 1 | Ontario | Toronto | North York | Parkwoods | 43.752777 | -79.326440 | Ranchdale Park | 43.751388 | -79.322138 | Park |
| 2 | Ontario | Toronto | North York | Parkwoods | 43.752777 | -79.326440 | S&A Tile & Flooring Services | 43.753928 | -79.320635 | Furniture / Home Store |
| 3 | Ontario | Toronto | North York | Victoria Village | 43.735735 | -79.312418 | Jatujak | 43.736208 | -79.307668 | Thai Restaurant |
| 4 | Ontario | Toronto | North York | Victoria Village | 43.735735 | -79.312418 | Artistic Nails | 43.736120 | -79.308080 | Spa |
| State | City | Borough | Neighborhood | Neighborhood Latitude | Neighborhood Longitude | Venue | Venue Latitude | Venue Longitude | Venue Category | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | New York | New York | Bronx | Melrose | 40.824545 | -73.910414 | Porto Salvo | 40.823887 | -73.912910 | Italian Restaurant |
| 1 | New York | New York | Bronx | Melrose | 40.824545 | -73.910414 | Perry Coffee Shop. | 40.823181 | -73.910928 | Diner |
| 2 | New York | New York | Bronx | Melrose | 40.824545 | -73.910414 | Cinco de Mayo | 40.822674 | -73.911592 | Mexican Restaurant |
| 3 | New York | New York | Bronx | Melrose | 40.824545 | -73.910414 | Old Bronx Courthouse | 40.822894 | -73.909565 | Art Gallery |
| 4 | New York | New York | Bronx | Melrose | 40.824545 | -73.910414 | Popeyes Louisiana Kitchen | 40.824605 | -73.909819 | Fried Chicken Joint |
| State | City | Borough | Neighborhood | Neighborhood Latitude | Neighborhood Longitude | Venue | Venue Latitude | Venue Longitude | Venue Category | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Illinois | Chicago | Far North Side | Loyola | 41.998948 | -87.658259 | 7-Eleven | 41.998363 | -87.659713 | Convenience Store |
| 1 | Illinois | Chicago | Far North Side | Loyola | 41.998948 | -87.658259 | Chase Bank | 41.998812 | -87.660245 | Bank |
| 2 | Illinois | Chicago | Far North Side | Loyola | 41.998948 | -87.658259 | Starbucks | 41.997897 | -87.660862 | Coffee Shop |
| 3 | Illinois | Chicago | Far North Side | Loyola | 41.998948 | -87.658259 | Nori | 41.998076 | -87.662075 | Sushi Restaurant |
| 4 | Illinois | Chicago | Far North Side | Loyola | 41.998948 | -87.658259 | Potbelly Sandwich Shop | 42.000031 | -87.660905 | Sandwich Place |
| State | City | Borough | Neighborhood | Neighborhood Latitude | Neighborhood Longitude | Venue | Venue Latitude | Venue Longitude | Venue Category | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Texas | Dallas | Downtown Dallas | Baylor District | 32.776282 | -96.797367 | Pioneer Plaza | 32.776616 | -96.801539 | Plaza |
| 1 | Texas | Dallas | Downtown Dallas | Baylor District | 32.776282 | -96.797367 | Spice in the City | 32.780014 | -96.797829 | Indian Restaurant |
| 2 | Texas | Dallas | Downtown Dallas | Baylor District | 32.776282 | -96.797367 | AT&T | 32.779811 | -96.798750 | Mobile Phone Shop |
| 3 | Texas | Dallas | Downtown Dallas | Baylor District | 32.776282 | -96.797367 | Aloft Dallas Downtown | 32.777186 | -96.801110 | Hotel |
| 4 | Texas | Dallas | Downtown Dallas | Baylor District | 32.776282 | -96.797367 | Weekend | 32.780309 | -96.798191 | Coffee Shop |
Let us see each city's neighborhood, which can be taken under consideration in very limited way, because there is no relevant information available.
Number of unexplorable neighborhoods: 20
| Unexplorable neighborhoods | ||
|---|---|---|
| State | City | |
| Illinois | Chicago | 3 |
| New York | New York | 1 |
| Ontario | Toronto | 1 |
| Texas | Dallas | 15 |
To find similarity between cities, their boroughs and neighborhoods we will analyze presence of venues in their neighborhoods grouped by venue categories. We will use k-means algorithm to find out similarity between neighborhoods and fit it with frequencies of presence venue categories in neighborhoods.
To compare objects we will use indicators as follow:
We will report results of the analysis for objects as follow:
Let us see how many unique venue categories were found.
There are 514 uniques venue categories.
Let us use one hot encoding and build relevant dataframe.
| State | City | Borough | Neighborhood | ATM | Accessories Store | Adult Boutique | Advertising Agency | Afghan Restaurant | African Restaurant | Airport | Airport Food Court | Airport Gate | Airport Lounge | Airport Service | Airport Terminal | American Restaurant | Amphitheater | Animal Shelter | Antique Shop | Aquarium | Arcade | Arepa Restaurant | Argentinian Restaurant | Art Gallery | Art Museum | Arts & Crafts Store | Arts & Entertainment | Asian Restaurant | Athletics & Sports | Auditorium | Australian Restaurant | Austrian Restaurant | Auto Dealership | Auto Garage | Auto Workshop | Automotive Shop | BBQ Joint | Baby Store | Bagel Shop | Bakery | Bank | Bar | Baseball Field | Baseball Stadium | Basketball Court | Basketball Stadium | Beach | Beach Bar | Bed & Breakfast | Beer Bar | Beer Garden | Beer Store | Belgian Restaurant | Big Box Store | Bike Rental / Bike Share | Bike Shop | Bike Trail | Bistro | Board Shop | Boat Rental | Boat or Ferry | Bookstore | Botanical Garden | Boutique | Bowling Alley | Boxing Gym | Brazilian Restaurant | Breakfast Spot | Brewery | Bridal Shop | Bridge | Bubble Tea Shop | Buffet | Building | Burger Joint | Burrito Place | Bus Line | Bus Station | Bus Stop | Business Service | Butcher | Cafeteria | Café | Cajun / Creole Restaurant | Cambodian Restaurant | Camera Store | Campground | Candy Store | Cantonese Restaurant | Caribbean Restaurant | Carpet Store | Caucasian Restaurant | Cemetery | Check Cashing Service | Cheese Shop | Child Care Service | Chinese Restaurant | Chiropractor | Chocolate Shop | Christmas Market | Church | Circus | Climbing Gym | Clothing Store | Club House | Cocktail Bar | Coffee Shop | College Academic Building | College Arts Building | College Auditorium | College Bookstore | College Cafeteria | College Gym | College Quad | College Rec Center | College Soccer Field | College Theater | College Track | Colombian Restaurant | Comedy Club | Comfort Food Restaurant | Comic Shop | Community Center | Concert Hall | Construction & Landscaping | Convenience Store | Cooking School | Cosmetics Shop | Costume Shop | Coworking Space | Creperie | Cuban Restaurant | Cultural Center | Cupcake Shop | Curling Ice | Currency Exchange | Cycle Studio | Czech Restaurant | Dance Studio | Daycare | Deli / Bodega | Dentist's Office | Department Store | Design Studio | Dessert Shop | Dim Sum Restaurant | Diner | Disc Golf | Discount Store | Distillery | Dive Bar | Doctor's Office | Dog Run | Doner Restaurant | Donut Shop | Dosa Place | Drugstore | Dry Cleaner | Dumpling Restaurant | Dutch Restaurant | Duty-free Shop | Eastern European Restaurant | Egyptian Restaurant | Electronics Store | Elementary School | Empanada Restaurant | English Restaurant | Entertainment Service | Ethiopian Restaurant | Event Service | Event Space | Exhibit | Eye Doctor | Fabric Shop | Factory | Falafel Restaurant | Farm | Farmers Market | Fast Food Restaurant | Festival | Field | Filipino Restaurant | Film Studio | Financial or Legal Service | Fish & Chips Shop | Fish Market | Fishing Store | Flea Market | Flower Shop | Fondue Restaurant | Food | Food & Drink Shop | Food Court | Food Service | Food Stand | Food Truck | Football Stadium | Fountain | Frame Store | French Restaurant | Fried Chicken Joint | Frozen Yogurt Shop | Fruit & Vegetable Store | Furniture / Home Store | Gaming Cafe | Garden | Garden Center | Gas Station | Gastropub | Gay Bar | General College & University | General Entertainment | General Travel | German Restaurant | Gift Shop | Gluten-free Restaurant | Golf Course | Golf Driving Range | Gourmet Shop | Greek Restaurant | Grocery Store | Gym | Gym / Fitness Center | Gym Pool | Gymnastics Gym | Halal Restaurant | Harbor / Marina | Hardware Store | Hawaiian Restaurant | Health & Beauty Service | Health Food Store | Heliport | Herbs & Spices Store | High School | Himalayan Restaurant | Historic Site | History Museum | Hobby Shop | Hockey Arena | Home Service | Hong Kong Restaurant | Hookah Bar | Hospital | Hostel | Hot Dog Joint | Hotel | Hotel Bar | Hotel Pool | Hotpot Restaurant | IT Services | Ice Cream Shop | Indian Chinese Restaurant | Indian Restaurant | Indie Movie Theater | Indie Theater | Indonesian Restaurant | Indoor Play Area | Insurance Office | Intersection | Irish Pub | Island | Israeli Restaurant | Italian Restaurant | Japanese Curry Restaurant | Japanese Restaurant | Jazz Club | Jewelry Store | Jewish Restaurant | Juice Bar | Karaoke Bar | Kebab Restaurant | Kids Store | Kitchen Supply Store | Korean Restaurant | Kosher Restaurant | Lake | Laser Tag | Latin American Restaurant | Laundromat | Laundry Service | Lawyer | Leather Goods Store | Lebanese Restaurant | Library | Light Rail Station | Lighthouse | Lingerie Store | Liquor Store | Locksmith | Lounge | Luggage Store | Mac & Cheese Joint | Malay Restaurant | Marijuana Dispensary | Market | Martial Arts Dojo | Massage Studio | Mattress Store | Medical Center | Medical Supply Store | Mediterranean Restaurant | Memorial Site | Men's Store | Metro Station | Mexican Restaurant | Middle Eastern Restaurant | Mini Golf | Miscellaneous Shop | Mobile Phone Shop | Modern European Restaurant | Modern Greek Restaurant | Molecular Gastronomy Restaurant | Monument / Landmark | Moroccan Restaurant | Motel | Motorcycle Shop | Movie Theater | Moving Target | Multiplex | Museum | Music School | Music Store | Music Venue | Nail Salon | Nature Preserve | Neighborhood VC | New American Restaurant | Newsstand | Nightclub | Non-Profit | Noodle House | North Indian Restaurant | Office | Opera House | Optical Shop | Organic Grocery | Other Great Outdoors | Other Nightlife | Other Repair Shop | Outdoor Sculpture | Outdoor Supply Store | Outdoors & Recreation | Outlet Store | Paella Restaurant | Pakistani Restaurant | Paper / Office Supplies Store | Park | Parking | Pastry Shop | Pawn Shop | Pedestrian Plaza | Peking Duck Restaurant | Performing Arts Venue | Persian Restaurant | Peruvian Restaurant | Pet Café | Pet Service | Pet Store | Pharmacy | Photography Lab | Photography Studio | Piano Bar | Pie Shop | Pier | Pilates Studio | Pizza Place | Planetarium | Platform | Playground | Plaza | Poke Place | Polish Restaurant | Pool | Pool Hall | Portuguese Restaurant | Poutine Place | Print Shop | Pub | Public Art | Racetrack | Ramen Restaurant | Record Shop | Recording Studio | Recreation Center | Rental Car Location | Rental Service | Residential Building (Apartment / Condo) | Resort | Rest Area | Restaurant | River | Road | Rock Climbing Spot | Rock Club | Roller Rink | Roof Deck | Russian Restaurant | Sake Bar | Salad Place | Salon / Barbershop | Salvadoran Restaurant | Sandwich Place | Scandinavian Restaurant | Scenic Lookout | School | Science Museum | Sculpture Garden | Seafood Restaurant | Shabu-Shabu Restaurant | Shanghai Restaurant | Shipping Store | Shoe Repair | Shoe Store | Shop & Service | Shopping Mall | Shopping Plaza | Skate Park | Skating Rink | Ski Lodge | Ski Shop | Smoke Shop | Smoothie Shop | Snack Place | Soba Restaurant | Soccer Field | Soccer Stadium | Social Club | Soup Place | South American Restaurant | South Indian Restaurant | Southern / Soul Food Restaurant | Souvenir Shop | Souvlaki Shop | Spa | Spanish Restaurant | Speakeasy | Sporting Goods Shop | Sports Bar | Sports Club | Sri Lankan Restaurant | Stables | Stadium | Stationery Store | Steakhouse | Storage Facility | Street Art | Street Food Gathering | Strip Club | Supermarket | Supplement Shop | Surf Spot | Sushi Restaurant | Swiss Restaurant | Synagogue | Syrian Restaurant | Szechuan Restaurant | Taco Place | Tailor Shop | Taiwanese Restaurant | Tanning Salon | Tapas Restaurant | Tattoo Parlor | Taxi Stand | Tea Room | Tech Startup | Tennis Court | Tennis Stadium | Tex-Mex Restaurant | Thai Restaurant | Theater | Theme Park | Theme Park Ride / Attraction | Theme Restaurant | Thrift / Vintage Store | Tibetan Restaurant | Tiki Bar | Toll Plaza | Tour Provider | Tourist Information Center | Toy / Game Store | Track | Track Stadium | Trade School | Trail | Train | Train Station | Tram Station | Travel Lounge | Tree | Tunnel | Turkish Restaurant | Udon Restaurant | Ukrainian Restaurant | University | Used Bookstore | Vacation Rental | Vape Store | Varenyky restaurant | Vegetarian / Vegan Restaurant | Venezuelan Restaurant | Veterinarian | Video Game Store | Video Store | Vietnamese Restaurant | Volleyball Court | Warehouse Store | Waste Facility | Waterfront | Weight Loss Center | Whisky Bar | Wine Bar | Wine Shop | Wings Joint | Women's Store | Yoga Studio | Zoo | Zoo Exhibit | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | New York | New York | Bronx | Melrose | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 1 | New York | New York | Bronx | Melrose | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2 | New York | New York | Bronx | Melrose | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 3 | New York | New York | Bronx | Melrose | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 4 | New York | New York | Bronx | Melrose | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Let us group rows by city's neighbourhood and by taking the mean of the frequency of occurrence of each venue category.
| State | City | Borough | Neighborhood | ATM | Accessories Store | Adult Boutique | Advertising Agency | Afghan Restaurant | African Restaurant | Airport | Airport Food Court | Airport Gate | Airport Lounge | Airport Service | Airport Terminal | American Restaurant | Amphitheater | Animal Shelter | Antique Shop | Aquarium | Arcade | Arepa Restaurant | Argentinian Restaurant | Art Gallery | Art Museum | Arts & Crafts Store | Arts & Entertainment | Asian Restaurant | Athletics & Sports | Auditorium | Australian Restaurant | Austrian Restaurant | Auto Dealership | Auto Garage | Auto Workshop | Automotive Shop | BBQ Joint | Baby Store | Bagel Shop | Bakery | Bank | Bar | Baseball Field | Baseball Stadium | Basketball Court | Basketball Stadium | Beach | Beach Bar | Bed & Breakfast | Beer Bar | Beer Garden | Beer Store | Belgian Restaurant | Big Box Store | Bike Rental / Bike Share | Bike Shop | Bike Trail | Bistro | Board Shop | Boat Rental | Boat or Ferry | Bookstore | Botanical Garden | Boutique | Bowling Alley | Boxing Gym | Brazilian Restaurant | Breakfast Spot | Brewery | Bridal Shop | Bridge | Bubble Tea Shop | Buffet | Building | Burger Joint | Burrito Place | Bus Line | Bus Station | Bus Stop | Business Service | Butcher | Cafeteria | Café | Cajun / Creole Restaurant | Cambodian Restaurant | Camera Store | Campground | Candy Store | Cantonese Restaurant | Caribbean Restaurant | Carpet Store | Caucasian Restaurant | Cemetery | Check Cashing Service | Cheese Shop | Child Care Service | Chinese Restaurant | Chiropractor | Chocolate Shop | Christmas Market | Church | Circus | Climbing Gym | Clothing Store | Club House | Cocktail Bar | Coffee Shop | College Academic Building | College Arts Building | College Auditorium | College Bookstore | College Cafeteria | College Gym | College Quad | College Rec Center | College Soccer Field | College Theater | College Track | Colombian Restaurant | Comedy Club | Comfort Food Restaurant | Comic Shop | Community Center | Concert Hall | Construction & Landscaping | Convenience Store | Cooking School | Cosmetics Shop | Costume Shop | Coworking Space | Creperie | Cuban Restaurant | Cultural Center | Cupcake Shop | Curling Ice | Currency Exchange | Cycle Studio | Czech Restaurant | Dance Studio | Daycare | Deli / Bodega | Dentist's Office | Department Store | Design Studio | Dessert Shop | Dim Sum Restaurant | Diner | Disc Golf | Discount Store | Distillery | Dive Bar | Doctor's Office | Dog Run | Doner Restaurant | Donut Shop | Dosa Place | Drugstore | Dry Cleaner | Dumpling Restaurant | Dutch Restaurant | Duty-free Shop | Eastern European Restaurant | Egyptian Restaurant | Electronics Store | Elementary School | Empanada Restaurant | English Restaurant | Entertainment Service | Ethiopian Restaurant | Event Service | Event Space | Exhibit | Eye Doctor | Fabric Shop | Factory | Falafel Restaurant | Farm | Farmers Market | Fast Food Restaurant | Festival | Field | Filipino Restaurant | Film Studio | Financial or Legal Service | Fish & Chips Shop | Fish Market | Fishing Store | Flea Market | Flower Shop | Fondue Restaurant | Food | Food & Drink Shop | Food Court | Food Service | Food Stand | Food Truck | Football Stadium | Fountain | Frame Store | French Restaurant | Fried Chicken Joint | Frozen Yogurt Shop | Fruit & Vegetable Store | Furniture / Home Store | Gaming Cafe | Garden | Garden Center | Gas Station | Gastropub | Gay Bar | General College & University | General Entertainment | General Travel | German Restaurant | Gift Shop | Gluten-free Restaurant | Golf Course | Golf Driving Range | Gourmet Shop | Greek Restaurant | Grocery Store | Gym | Gym / Fitness Center | Gym Pool | Gymnastics Gym | Halal Restaurant | Harbor / Marina | Hardware Store | Hawaiian Restaurant | Health & Beauty Service | Health Food Store | Heliport | Herbs & Spices Store | High School | Himalayan Restaurant | Historic Site | History Museum | Hobby Shop | Hockey Arena | Home Service | Hong Kong Restaurant | Hookah Bar | Hospital | Hostel | Hot Dog Joint | Hotel | Hotel Bar | Hotel Pool | Hotpot Restaurant | IT Services | Ice Cream Shop | Indian Chinese Restaurant | Indian Restaurant | Indie Movie Theater | Indie Theater | Indonesian Restaurant | Indoor Play Area | Insurance Office | Intersection | Irish Pub | Island | Israeli Restaurant | Italian Restaurant | Japanese Curry Restaurant | Japanese Restaurant | Jazz Club | Jewelry Store | Jewish Restaurant | Juice Bar | Karaoke Bar | Kebab Restaurant | Kids Store | Kitchen Supply Store | Korean Restaurant | Kosher Restaurant | Lake | Laser Tag | Latin American Restaurant | Laundromat | Laundry Service | Lawyer | Leather Goods Store | Lebanese Restaurant | Library | Light Rail Station | Lighthouse | Lingerie Store | Liquor Store | Locksmith | Lounge | Luggage Store | Mac & Cheese Joint | Malay Restaurant | Marijuana Dispensary | Market | Martial Arts Dojo | Massage Studio | Mattress Store | Medical Center | Medical Supply Store | Mediterranean Restaurant | Memorial Site | Men's Store | Metro Station | Mexican Restaurant | Middle Eastern Restaurant | Mini Golf | Miscellaneous Shop | Mobile Phone Shop | Modern European Restaurant | Modern Greek Restaurant | Molecular Gastronomy Restaurant | Monument / Landmark | Moroccan Restaurant | Motel | Motorcycle Shop | Movie Theater | Moving Target | Multiplex | Museum | Music School | Music Store | Music Venue | Nail Salon | Nature Preserve | Neighborhood VC | New American Restaurant | Newsstand | Nightclub | Non-Profit | Noodle House | North Indian Restaurant | Office | Opera House | Optical Shop | Organic Grocery | Other Great Outdoors | Other Nightlife | Other Repair Shop | Outdoor Sculpture | Outdoor Supply Store | Outdoors & Recreation | Outlet Store | Paella Restaurant | Pakistani Restaurant | Paper / Office Supplies Store | Park | Parking | Pastry Shop | Pawn Shop | Pedestrian Plaza | Peking Duck Restaurant | Performing Arts Venue | Persian Restaurant | Peruvian Restaurant | Pet Café | Pet Service | Pet Store | Pharmacy | Photography Lab | Photography Studio | Piano Bar | Pie Shop | Pier | Pilates Studio | Pizza Place | Planetarium | Platform | Playground | Plaza | Poke Place | Polish Restaurant | Pool | Pool Hall | Portuguese Restaurant | Poutine Place | Print Shop | Pub | Public Art | Racetrack | Ramen Restaurant | Record Shop | Recording Studio | Recreation Center | Rental Car Location | Rental Service | Residential Building (Apartment / Condo) | Resort | Rest Area | Restaurant | River | Road | Rock Climbing Spot | Rock Club | Roller Rink | Roof Deck | Russian Restaurant | Sake Bar | Salad Place | Salon / Barbershop | Salvadoran Restaurant | Sandwich Place | Scandinavian Restaurant | Scenic Lookout | School | Science Museum | Sculpture Garden | Seafood Restaurant | Shabu-Shabu Restaurant | Shanghai Restaurant | Shipping Store | Shoe Repair | Shoe Store | Shop & Service | Shopping Mall | Shopping Plaza | Skate Park | Skating Rink | Ski Lodge | Ski Shop | Smoke Shop | Smoothie Shop | Snack Place | Soba Restaurant | Soccer Field | Soccer Stadium | Social Club | Soup Place | South American Restaurant | South Indian Restaurant | Southern / Soul Food Restaurant | Souvenir Shop | Souvlaki Shop | Spa | Spanish Restaurant | Speakeasy | Sporting Goods Shop | Sports Bar | Sports Club | Sri Lankan Restaurant | Stables | Stadium | Stationery Store | Steakhouse | Storage Facility | Street Art | Street Food Gathering | Strip Club | Supermarket | Supplement Shop | Surf Spot | Sushi Restaurant | Swiss Restaurant | Synagogue | Syrian Restaurant | Szechuan Restaurant | Taco Place | Tailor Shop | Taiwanese Restaurant | Tanning Salon | Tapas Restaurant | Tattoo Parlor | Taxi Stand | Tea Room | Tech Startup | Tennis Court | Tennis Stadium | Tex-Mex Restaurant | Thai Restaurant | Theater | Theme Park | Theme Park Ride / Attraction | Theme Restaurant | Thrift / Vintage Store | Tibetan Restaurant | Tiki Bar | Toll Plaza | Tour Provider | Tourist Information Center | Toy / Game Store | Track | Track Stadium | Trade School | Trail | Train | Train Station | Tram Station | Travel Lounge | Tree | Tunnel | Turkish Restaurant | Udon Restaurant | Ukrainian Restaurant | University | Used Bookstore | Vacation Rental | Vape Store | Varenyky restaurant | Vegetarian / Vegan Restaurant | Venezuelan Restaurant | Veterinarian | Video Game Store | Video Store | Vietnamese Restaurant | Volleyball Court | Warehouse Store | Waste Facility | Waterfront | Weight Loss Center | Whisky Bar | Wine Bar | Wine Shop | Wings Joint | Women's Store | Yoga Studio | Zoo | Zoo Exhibit | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Illinois | Chicago | Central | Cabrini–Green | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.041667 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.041667 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.041667 | 0.041667 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.083333 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.041667 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.041667 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.041667 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.041667 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.041667 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.083333 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.041667 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.041667 | 0.0 | 0.0 | 0.041667 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.041667 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.041667 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.041667 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.041667 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.041667 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.041667 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.041667 | 0.041667 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 |
| 1 | Illinois | Chicago | Central | Central Station | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.035714 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.017857 | 0.017857 | 0.017857 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.017857 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.017857 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.035714 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.017857 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.017857 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.017857 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.017857 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.017857 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.017857 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.017857 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.017857 | 0.017857 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.035714 | 0.196429 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.017857 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.017857 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.017857 | 0.0 | 0.000000 | 0.053571 | 0.0 | 0.017857 | 0.017857 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.017857 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.017857 | 0.017857 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.017857 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.035714 | 0.0 | 0.0 | 0.017857 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.017857 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.017857 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.017857 | 0.0 | 0.017857 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.017857 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.017857 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.017857 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.017857 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.017857 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.017857 | 0.0 | 0.0 |
| 2 | Illinois | Chicago | Central | Dearborn Park | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.023256 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.034884 | 0.0 | 0.0 | 0.023256 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.011628 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.034884 | 0.0 | 0.000000 | 0.058140 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.011628 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.023256 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.034884 | 0.023256 | 0.046512 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.0 | 0.023256 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.023256 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.011628 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.023256 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.0 | 0.023256 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.011628 | 0.011628 | 0.0 | 0.011628 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.023256 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.000000 | 0.011628 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.034884 | 0.0 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.011628 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.0 | 0.046512 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.011628 | 0.000000 | 0.0 | 0.0 | 0.011628 | 0.0 | 0.000000 | 0.0 | 0.011628 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.011628 | 0.011628 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.000000 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.011628 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.011628 | 0.023256 | 0.0 | 0.0 |
| 3 | Illinois | Chicago | Central | Gold Coast | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.041667 | 0.0 | 0.0 | 0.013889 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.013889 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.013889 | 0.000000 | 0.0 | 0.000000 | 0.013889 | 0.041667 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.013889 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.013889 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.013889 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.041667 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.013889 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.013889 | 0.0 | 0.013889 | 0.041667 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.013889 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.013889 | 0.013889 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.013889 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.041667 | 0.027778 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.013889 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.013889 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.027778 | 0.013889 | 0.0 | 0.0 | 0.0 | 0.013889 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.069444 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.027778 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.027778 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.013889 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.013889 | 0.0 | 0.013889 | 0.013889 | 0.0 | 0.0 | 0.0 | 0.0 | 0.013889 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.013889 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.013889 | 0.0 | 0.0 | 0.013889 | 0.0 | 0.0 | 0.0 | 0.027778 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.013889 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.027778 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.013889 | 0.0 | 0.013889 | 0.0 | 0.0 | 0.0 | 0.013889 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.013889 | 0.0 | 0.013889 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.041667 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.013889 | 0.0 | 0.013889 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.013889 | 0.000000 | 0.027778 | 0.0 | 0.0 |
| 4 | Illinois | Chicago | Central | Goose Island | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.058824 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.058824 | 0.0 | 0.000000 | 0.000000 | 0.058824 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.058824 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.058824 | 0.0 | 0.0 | 0.058824 | 0.0 | 0.0 | 0.0 | 0.0 | 0.058824 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.058824 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.058824 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.058824 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.058824 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.058824 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.058824 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.058824 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.058824 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.058824 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.0 | 0.058824 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.000000 | 0.000000 | 0.0 | 0.0 |
Let us find out the most common 10 venue categories for each city's neighbourhood.
| State | City | Borough | Neighborhood | 1st Most Common Venue | 2nd Most Common Venue | 3rd Most Common Venue | 4th Most Common Venue | 5th Most Common Venue | 6th Most Common Venue | 7th Most Common Venue | 8th Most Common Venue | 9th Most Common Venue | 10th Most Common Venue | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Illinois | Chicago | Central | Cabrini–Green | Lounge | Coffee Shop | Supermarket | Fast Food Restaurant | Bakery | Outdoors & Recreation | Gym | Shipping Store | Mediterranean Restaurant | Big Box Store |
| 1 | Illinois | Chicago | Central | Central Station | History Museum | Museum | American Restaurant | Pizza Place | Burger Joint | Historic Site | Gift Shop | Breakfast Spot | Dog Run | Sushi Restaurant |
| 2 | Illinois | Chicago | Central | Dearborn Park | Coffee Shop | Gym / Fitness Center | Sandwich Place | Pizza Place | Clothing Store | Grocery Store | Burger Joint | Italian Restaurant | Gym | Asian Restaurant |
| 3 | Illinois | Chicago | Central | Gold Coast | Italian Restaurant | Gym | Bar | Café | Steakhouse | American Restaurant | Coffee Shop | Massage Studio | Gym / Fitness Center | Hotel |
| 4 | Illinois | Chicago | Central | Goose Island | Burger Joint | Café | Baby Store | Outdoor Supply Store | Seafood Restaurant | Pet Store | Donut Shop | Arts & Entertainment | Sandwich Place | Kitchen Supply Store |
Let us use k-means algorithm to find out optimal number of centroids for clustering city's neighborhoods.
k-means algorithm is known to fluctuation because of randomly chosen centroids and presence of local minimas. To reduce that fluctuation we execute it few times using different random state. At the end one random state will be chosen, that one which gives the highest Silhouette score for analyzed data.
It seems, that all neighborhoods are rather similar each to other. The best Silhouette score is 0.5455, higher than 0.5, all clusters have Silhouette score for their data points higher than that one for entire data. So, for the comparison we choose 3 clusters, even the cluster labelled with 0 is signigicantly bigger than other ones.
The Elbow method does not clearly show the proper clusters number, so we will follow results given by Silhouette method.
Let us apply clustering to all neighbourhoods. Note, that there is some unexplorable neighborhoods, which were mentioned earlier, they will be added and labelled with -1.
Let us compare numer of city's neighborhoods according to labelling they get.
| Cluster Label | -1 | 0 | 1 | 2 | |||
|---|---|---|---|---|---|---|---|
| State | City | Borough | Neighborhood | ||||
| Illinois | Chicago | Central | Cabrini–Green | 0 | 1 | 0 | 0 |
| Central Station | 0 | 1 | 0 | 0 | |||
| Dearborn Park | 0 | 1 | 0 | 0 | |||
| Gold Coast | 0 | 1 | 0 | 0 | |||
| Goose Island | 0 | 1 | 0 | 0 | |||
| Loop | 0 | 1 | 0 | 0 | |||
| Magnificent Mile | 0 | 1 | 0 | 0 | |||
| Museum Campus | 0 | 1 | 0 | 0 | |||
| Near North Side | 0 | 1 | 0 | 0 | |||
| New Eastside | 0 | 1 | 0 | 0 | |||
| Old Town | 0 | 1 | 0 | 0 | |||
| Prairie Avenue Historic District | 0 | 1 | 0 | 0 | |||
| Printer's Row | 0 | 1 | 0 | 0 | |||
| River North | 0 | 1 | 0 | 0 | |||
| South Loop | 0 | 1 | 0 | 0 | |||
| Streeterville | 0 | 1 | 0 | 0 | |||
| Far North Side | Albany Park | 0 | 1 | 0 | 0 | ||
| Andersonville | 0 | 1 | 0 | 0 | |||
| Big Oaks | 0 | 1 | 0 | 0 | |||
| Bowmanville | 0 | 1 | 0 | 0 | |||
| Budlong Woods | 0 | 1 | 0 | 0 | |||
| Buena Park | 0 | 1 | 0 | 0 | |||
| Clarendon Park | 0 | 1 | 0 | 0 | |||
| Edgebrook | 0 | 1 | 0 | 0 | |||
| Edgewater | 0 | 1 | 0 | 0 | |||
| Edgewater Beach | 0 | 1 | 0 | 0 | |||
| Edgewater Glen | 0 | 1 | 0 | 0 | |||
| Edison Park | 0 | 1 | 0 | 0 | |||
| Forest Glen | 0 | 1 | 0 | 0 | |||
| Gladstone Park | 0 | 1 | 0 | 0 | |||
| Hollywood Park | 0 | 1 | 0 | 0 | |||
| Jefferson Park | 0 | 1 | 0 | 0 | |||
| Lakewood / Balmoral | 0 | 1 | 0 | 0 | |||
| Lincoln Square | 0 | 1 | 0 | 0 | |||
| Loyola | 0 | 1 | 0 | 0 | |||
| Margate Park | 0 | 1 | 0 | 0 | |||
| Mayfair | 0 | 1 | 0 | 0 | |||
| New Chinatown | 0 | 1 | 0 | 0 | |||
| North Mayfair | 0 | 1 | 0 | 0 | |||
| North Park | 0 | 1 | 0 | 0 | |||
| Nortown | 0 | 1 | 0 | 0 | |||
| Norwood Park East | 0 | 1 | 0 | 0 | |||
| Norwood Park West | 0 | 1 | 0 | 0 | |||
| O'Hare | 0 | 1 | 0 | 0 | |||
| Old Edgebrook | 0 | 1 | 0 | 0 | |||
| Old Norwood | 0 | 1 | 0 | 0 | |||
| Oriole Park | 0 | 1 | 0 | 0 | |||
| Peterson Park | 0 | 1 | 0 | 0 | |||
| Ravenswood | 0 | 1 | 0 | 0 | |||
| Ravenswood Gardens | 0 | 1 | 0 | 0 |
Let us compare numer of city's neighborhoods according to labelling they get grouping by city's boroughs.
| Cluster Label | -1 | 0 | 1 | 2 | ||
|---|---|---|---|---|---|---|
| State | City | Borough | ||||
| Illinois | Chicago | Central | 0 | 16 | 0 | 0 |
| Far North Side | 0 | 47 | 0 | 0 | ||
| Far Southeast Side | 3 | 24 | 0 | 0 | ||
| Far Southwest Side | 0 | 21 | 0 | 0 | ||
| North Side | 0 | 27 | 0 | 0 | ||
| Northwest Side | 0 | 20 | 0 | 0 | ||
| South Side | 0 | 28 | 0 | 0 | ||
| Southwest Side | 0 | 23 | 0 | 0 | ||
| West Side | 0 | 37 | 0 | 0 | ||
| New York | New York | Bronx | 0 | 60 | 0 | 0 |
| Brooklyn | 0 | 79 | 0 | 0 | ||
| Manhattan | 0 | 47 | 0 | 0 | ||
| Queens | 0 | 86 | 0 | 0 | ||
| Staten Island | 1 | 55 | 0 | 0 | ||
| Ontario | Toronto | Central Toronto | 0 | 17 | 0 | 0 |
| Downtown Toronto | 0 | 37 | 0 | 0 | ||
| East Toronto | 0 | 7 | 0 | 0 | ||
| East York | 0 | 6 | 0 | 0 | ||
| Etobicoke | 1 | 43 | 0 | 0 | ||
| Mississauga | 0 | 1 | 0 | 0 | ||
| North York | 0 | 35 | 3 | 0 | ||
| Queen's Park | 0 | 1 | 0 | 0 | ||
| Scarborough | 0 | 37 | 0 | 0 | ||
| West Toronto | 0 | 13 | 0 | 0 | ||
| York | 0 | 9 | 0 | 0 | ||
| Texas | Dallas | Downtown Dallas | 0 | 15 | 0 | 0 |
| East Dallas | 1 | 33 | 0 | 0 | ||
| Fair Park | 0 | 12 | 0 | 0 | ||
| Far North Dallas | 1 | 6 | 0 | 0 | ||
| Far South Dallas | 0 | 3 | 0 | 0 | ||
| North Dallas | 1 | 7 | 0 | 0 | ||
| Northeast Dallas | 6 | 36 | 0 | 0 | ||
| Northwest Dallas | 0 | 7 | 0 | 0 | ||
| Oak Cliff Area | 0 | 19 | 0 | 0 | ||
| Oak Lawn | 0 | 11 | 0 | 0 | ||
| Old East Dallas | 1 | 6 | 0 | 0 | ||
| Redbird | 1 | 3 | 0 | 0 | ||
| South Central Dallas | 0 | 2 | 0 | 0 | ||
| Southeast Dallas | 2 | 10 | 0 | 9 | ||
| West Dallas | 2 | 9 | 0 | 0 |
Let us compare numer of city's neighborhoods according to labelling they get grouping by cities.
| Cluster Label | -1 | 0 | 1 | 2 | |
|---|---|---|---|---|---|
| State | City | ||||
| Illinois | Chicago | 3 | 243 | 0 | 0 |
| New York | New York | 1 | 327 | 0 | 0 |
| Ontario | Toronto | 1 | 206 | 3 | 0 |
| Texas | Dallas | 15 | 179 | 0 | 9 |
Let us compare similarity of objects by calculating distance between them. Each object features, which are taken for distance calculation, are its cluster labels.
Let us compare similarity of cities.
| Cluster Label | -1 | 0 | 1 | 2 | Distance | |
|---|---|---|---|---|---|---|
| State | City | |||||
| Ontario | Toronto | 0.004762 | 0.980952 | 0.014286 | 0.000000 | 0.000000 |
| Illinois | Chicago | 0.012195 | 0.987805 | 0.000000 | 0.000000 | 0.017501 |
| New York | New York | 0.003049 | 0.996951 | 0.000000 | 0.000000 | 0.021517 |
| Texas | Dallas | 0.073892 | 0.881773 | 0.000000 | 0.044335 | 0.129557 |
List of cities in the most similar to Toronto, Ontario, which the employee comes from:
Let us compare similarity of city's boroughs.
| Employee State | Employee City | Employee Borough | State | City | Borough | Distance | |
|---|---|---|---|---|---|---|---|
| 0 | Ontario | Toronto | Central Toronto | Illinois | Chicago | Central | 0.0 |
| 29 | Ontario | Toronto | Downtown Toronto | Illinois | Chicago | Central | 0.0 |
| 58 | Ontario | Toronto | East Toronto | Illinois | Chicago | Central | 0.0 |
| 87 | Ontario | Toronto | East York | Illinois | Chicago | Central | 0.0 |
| 145 | Ontario | Toronto | Mississauga | Illinois | Chicago | Central | 0.0 |
| 203 | Ontario | Toronto | Queen's Park | Illinois | Chicago | Central | 0.0 |
| 232 | Ontario | Toronto | Scarborough | Illinois | Chicago | Central | 0.0 |
| 261 | Ontario | Toronto | West Toronto | Illinois | Chicago | Central | 0.0 |
| 290 | Ontario | Toronto | York | Illinois | Chicago | Central | 0.0 |
| 1 | Ontario | Toronto | Central Toronto | Illinois | Chicago | Far North Side | 0.0 |
| 30 | Ontario | Toronto | Downtown Toronto | Illinois | Chicago | Far North Side | 0.0 |
| 59 | Ontario | Toronto | East Toronto | Illinois | Chicago | Far North Side | 0.0 |
| 88 | Ontario | Toronto | East York | Illinois | Chicago | Far North Side | 0.0 |
| 146 | Ontario | Toronto | Mississauga | Illinois | Chicago | Far North Side | 0.0 |
| 204 | Ontario | Toronto | Queen's Park | Illinois | Chicago | Far North Side | 0.0 |
| 233 | Ontario | Toronto | Scarborough | Illinois | Chicago | Far North Side | 0.0 |
| 262 | Ontario | Toronto | West Toronto | Illinois | Chicago | Far North Side | 0.0 |
| 291 | Ontario | Toronto | York | Illinois | Chicago | Far North Side | 0.0 |
| 3 | Ontario | Toronto | Central Toronto | Illinois | Chicago | Far Southwest Side | 0.0 |
| 32 | Ontario | Toronto | Downtown Toronto | Illinois | Chicago | Far Southwest Side | 0.0 |
| 61 | Ontario | Toronto | East Toronto | Illinois | Chicago | Far Southwest Side | 0.0 |
| 90 | Ontario | Toronto | East York | Illinois | Chicago | Far Southwest Side | 0.0 |
| 148 | Ontario | Toronto | Mississauga | Illinois | Chicago | Far Southwest Side | 0.0 |
| 206 | Ontario | Toronto | Queen's Park | Illinois | Chicago | Far Southwest Side | 0.0 |
| 235 | Ontario | Toronto | Scarborough | Illinois | Chicago | Far Southwest Side | 0.0 |
| 264 | Ontario | Toronto | West Toronto | Illinois | Chicago | Far Southwest Side | 0.0 |
| 293 | Ontario | Toronto | York | Illinois | Chicago | Far Southwest Side | 0.0 |
| 4 | Ontario | Toronto | Central Toronto | Illinois | Chicago | North Side | 0.0 |
| 33 | Ontario | Toronto | Downtown Toronto | Illinois | Chicago | North Side | 0.0 |
| 62 | Ontario | Toronto | East Toronto | Illinois | Chicago | North Side | 0.0 |
| 91 | Ontario | Toronto | East York | Illinois | Chicago | North Side | 0.0 |
| 149 | Ontario | Toronto | Mississauga | Illinois | Chicago | North Side | 0.0 |
| 207 | Ontario | Toronto | Queen's Park | Illinois | Chicago | North Side | 0.0 |
| 236 | Ontario | Toronto | Scarborough | Illinois | Chicago | North Side | 0.0 |
| 265 | Ontario | Toronto | West Toronto | Illinois | Chicago | North Side | 0.0 |
| 294 | Ontario | Toronto | York | Illinois | Chicago | North Side | 0.0 |
| 5 | Ontario | Toronto | Central Toronto | Illinois | Chicago | Northwest Side | 0.0 |
| 34 | Ontario | Toronto | Downtown Toronto | Illinois | Chicago | Northwest Side | 0.0 |
| 63 | Ontario | Toronto | East Toronto | Illinois | Chicago | Northwest Side | 0.0 |
| 92 | Ontario | Toronto | East York | Illinois | Chicago | Northwest Side | 0.0 |
| 150 | Ontario | Toronto | Mississauga | Illinois | Chicago | Northwest Side | 0.0 |
| 208 | Ontario | Toronto | Queen's Park | Illinois | Chicago | Northwest Side | 0.0 |
| 237 | Ontario | Toronto | Scarborough | Illinois | Chicago | Northwest Side | 0.0 |
| 266 | Ontario | Toronto | West Toronto | Illinois | Chicago | Northwest Side | 0.0 |
| 295 | Ontario | Toronto | York | Illinois | Chicago | Northwest Side | 0.0 |
| 6 | Ontario | Toronto | Central Toronto | Illinois | Chicago | South Side | 0.0 |
| 35 | Ontario | Toronto | Downtown Toronto | Illinois | Chicago | South Side | 0.0 |
| 64 | Ontario | Toronto | East Toronto | Illinois | Chicago | South Side | 0.0 |
| 93 | Ontario | Toronto | East York | Illinois | Chicago | South Side | 0.0 |
| 151 | Ontario | Toronto | Mississauga | Illinois | Chicago | South Side | 0.0 |
| 209 | Ontario | Toronto | Queen's Park | Illinois | Chicago | South Side | 0.0 |
| 238 | Ontario | Toronto | Scarborough | Illinois | Chicago | South Side | 0.0 |
| 267 | Ontario | Toronto | West Toronto | Illinois | Chicago | South Side | 0.0 |
| 296 | Ontario | Toronto | York | Illinois | Chicago | South Side | 0.0 |
| 7 | Ontario | Toronto | Central Toronto | Illinois | Chicago | Southwest Side | 0.0 |
| 36 | Ontario | Toronto | Downtown Toronto | Illinois | Chicago | Southwest Side | 0.0 |
| 65 | Ontario | Toronto | East Toronto | Illinois | Chicago | Southwest Side | 0.0 |
| 94 | Ontario | Toronto | East York | Illinois | Chicago | Southwest Side | 0.0 |
| 152 | Ontario | Toronto | Mississauga | Illinois | Chicago | Southwest Side | 0.0 |
| 210 | Ontario | Toronto | Queen's Park | Illinois | Chicago | Southwest Side | 0.0 |
| 239 | Ontario | Toronto | Scarborough | Illinois | Chicago | Southwest Side | 0.0 |
| 268 | Ontario | Toronto | West Toronto | Illinois | Chicago | Southwest Side | 0.0 |
| 297 | Ontario | Toronto | York | Illinois | Chicago | Southwest Side | 0.0 |
| 8 | Ontario | Toronto | Central Toronto | Illinois | Chicago | West Side | 0.0 |
| 37 | Ontario | Toronto | Downtown Toronto | Illinois | Chicago | West Side | 0.0 |
| 66 | Ontario | Toronto | East Toronto | Illinois | Chicago | West Side | 0.0 |
| 95 | Ontario | Toronto | East York | Illinois | Chicago | West Side | 0.0 |
| 153 | Ontario | Toronto | Mississauga | Illinois | Chicago | West Side | 0.0 |
| 211 | Ontario | Toronto | Queen's Park | Illinois | Chicago | West Side | 0.0 |
| 240 | Ontario | Toronto | Scarborough | Illinois | Chicago | West Side | 0.0 |
| 269 | Ontario | Toronto | West Toronto | Illinois | Chicago | West Side | 0.0 |
| 298 | Ontario | Toronto | York | Illinois | Chicago | West Side | 0.0 |
| 9 | Ontario | Toronto | Central Toronto | New York | New York | Bronx | 0.0 |
| 38 | Ontario | Toronto | Downtown Toronto | New York | New York | Bronx | 0.0 |
| 67 | Ontario | Toronto | East Toronto | New York | New York | Bronx | 0.0 |
| 96 | Ontario | Toronto | East York | New York | New York | Bronx | 0.0 |
| 154 | Ontario | Toronto | Mississauga | New York | New York | Bronx | 0.0 |
| 212 | Ontario | Toronto | Queen's Park | New York | New York | Bronx | 0.0 |
| 241 | Ontario | Toronto | Scarborough | New York | New York | Bronx | 0.0 |
| 270 | Ontario | Toronto | West Toronto | New York | New York | Bronx | 0.0 |
| 299 | Ontario | Toronto | York | New York | New York | Bronx | 0.0 |
| 10 | Ontario | Toronto | Central Toronto | New York | New York | Brooklyn | 0.0 |
| 39 | Ontario | Toronto | Downtown Toronto | New York | New York | Brooklyn | 0.0 |
| 68 | Ontario | Toronto | East Toronto | New York | New York | Brooklyn | 0.0 |
| 97 | Ontario | Toronto | East York | New York | New York | Brooklyn | 0.0 |
| 155 | Ontario | Toronto | Mississauga | New York | New York | Brooklyn | 0.0 |
| 213 | Ontario | Toronto | Queen's Park | New York | New York | Brooklyn | 0.0 |
| 242 | Ontario | Toronto | Scarborough | New York | New York | Brooklyn | 0.0 |
| 271 | Ontario | Toronto | West Toronto | New York | New York | Brooklyn | 0.0 |
| 300 | Ontario | Toronto | York | New York | New York | Brooklyn | 0.0 |
| 11 | Ontario | Toronto | Central Toronto | New York | New York | Manhattan | 0.0 |
| 40 | Ontario | Toronto | Downtown Toronto | New York | New York | Manhattan | 0.0 |
| 69 | Ontario | Toronto | East Toronto | New York | New York | Manhattan | 0.0 |
| 98 | Ontario | Toronto | East York | New York | New York | Manhattan | 0.0 |
| 156 | Ontario | Toronto | Mississauga | New York | New York | Manhattan | 0.0 |
| 214 | Ontario | Toronto | Queen's Park | New York | New York | Manhattan | 0.0 |
| 243 | Ontario | Toronto | Scarborough | New York | New York | Manhattan | 0.0 |
| 272 | Ontario | Toronto | West Toronto | New York | New York | Manhattan | 0.0 |
| 301 | Ontario | Toronto | York | New York | New York | Manhattan | 0.0 |
| 12 | Ontario | Toronto | Central Toronto | New York | New York | Queens | 0.0 |
| 41 | Ontario | Toronto | Downtown Toronto | New York | New York | Queens | 0.0 |
| 70 | Ontario | Toronto | East Toronto | New York | New York | Queens | 0.0 |
| 99 | Ontario | Toronto | East York | New York | New York | Queens | 0.0 |
| 157 | Ontario | Toronto | Mississauga | New York | New York | Queens | 0.0 |
| 215 | Ontario | Toronto | Queen's Park | New York | New York | Queens | 0.0 |
| 244 | Ontario | Toronto | Scarborough | New York | New York | Queens | 0.0 |
| 273 | Ontario | Toronto | West Toronto | New York | New York | Queens | 0.0 |
| 302 | Ontario | Toronto | York | New York | New York | Queens | 0.0 |
| 14 | Ontario | Toronto | Central Toronto | Texas | Dallas | Downtown Dallas | 0.0 |
| 43 | Ontario | Toronto | Downtown Toronto | Texas | Dallas | Downtown Dallas | 0.0 |
| 72 | Ontario | Toronto | East Toronto | Texas | Dallas | Downtown Dallas | 0.0 |
| 101 | Ontario | Toronto | East York | Texas | Dallas | Downtown Dallas | 0.0 |
| 159 | Ontario | Toronto | Mississauga | Texas | Dallas | Downtown Dallas | 0.0 |
| 217 | Ontario | Toronto | Queen's Park | Texas | Dallas | Downtown Dallas | 0.0 |
| 246 | Ontario | Toronto | Scarborough | Texas | Dallas | Downtown Dallas | 0.0 |
| 275 | Ontario | Toronto | West Toronto | Texas | Dallas | Downtown Dallas | 0.0 |
| 304 | Ontario | Toronto | York | Texas | Dallas | Downtown Dallas | 0.0 |
| 16 | Ontario | Toronto | Central Toronto | Texas | Dallas | Fair Park | 0.0 |
| 45 | Ontario | Toronto | Downtown Toronto | Texas | Dallas | Fair Park | 0.0 |
| 74 | Ontario | Toronto | East Toronto | Texas | Dallas | Fair Park | 0.0 |
| 103 | Ontario | Toronto | East York | Texas | Dallas | Fair Park | 0.0 |
| 161 | Ontario | Toronto | Mississauga | Texas | Dallas | Fair Park | 0.0 |
| 219 | Ontario | Toronto | Queen's Park | Texas | Dallas | Fair Park | 0.0 |
| 248 | Ontario | Toronto | Scarborough | Texas | Dallas | Fair Park | 0.0 |
| 277 | Ontario | Toronto | West Toronto | Texas | Dallas | Fair Park | 0.0 |
| 306 | Ontario | Toronto | York | Texas | Dallas | Fair Park | 0.0 |
| 18 | Ontario | Toronto | Central Toronto | Texas | Dallas | Far South Dallas | 0.0 |
| 47 | Ontario | Toronto | Downtown Toronto | Texas | Dallas | Far South Dallas | 0.0 |
| 76 | Ontario | Toronto | East Toronto | Texas | Dallas | Far South Dallas | 0.0 |
| 105 | Ontario | Toronto | East York | Texas | Dallas | Far South Dallas | 0.0 |
| 163 | Ontario | Toronto | Mississauga | Texas | Dallas | Far South Dallas | 0.0 |
| 221 | Ontario | Toronto | Queen's Park | Texas | Dallas | Far South Dallas | 0.0 |
| 250 | Ontario | Toronto | Scarborough | Texas | Dallas | Far South Dallas | 0.0 |
| 279 | Ontario | Toronto | West Toronto | Texas | Dallas | Far South Dallas | 0.0 |
| 308 | Ontario | Toronto | York | Texas | Dallas | Far South Dallas | 0.0 |
| 21 | Ontario | Toronto | Central Toronto | Texas | Dallas | Northwest Dallas | 0.0 |
| 50 | Ontario | Toronto | Downtown Toronto | Texas | Dallas | Northwest Dallas | 0.0 |
| 79 | Ontario | Toronto | East Toronto | Texas | Dallas | Northwest Dallas | 0.0 |
| 108 | Ontario | Toronto | East York | Texas | Dallas | Northwest Dallas | 0.0 |
| 166 | Ontario | Toronto | Mississauga | Texas | Dallas | Northwest Dallas | 0.0 |
| 224 | Ontario | Toronto | Queen's Park | Texas | Dallas | Northwest Dallas | 0.0 |
| 253 | Ontario | Toronto | Scarborough | Texas | Dallas | Northwest Dallas | 0.0 |
| 282 | Ontario | Toronto | West Toronto | Texas | Dallas | Northwest Dallas | 0.0 |
| 311 | Ontario | Toronto | York | Texas | Dallas | Northwest Dallas | 0.0 |
| 22 | Ontario | Toronto | Central Toronto | Texas | Dallas | Oak Cliff Area | 0.0 |
| 51 | Ontario | Toronto | Downtown Toronto | Texas | Dallas | Oak Cliff Area | 0.0 |
| 80 | Ontario | Toronto | East Toronto | Texas | Dallas | Oak Cliff Area | 0.0 |
| 109 | Ontario | Toronto | East York | Texas | Dallas | Oak Cliff Area | 0.0 |
| 167 | Ontario | Toronto | Mississauga | Texas | Dallas | Oak Cliff Area | 0.0 |
| 225 | Ontario | Toronto | Queen's Park | Texas | Dallas | Oak Cliff Area | 0.0 |
| 254 | Ontario | Toronto | Scarborough | Texas | Dallas | Oak Cliff Area | 0.0 |
| 283 | Ontario | Toronto | West Toronto | Texas | Dallas | Oak Cliff Area | 0.0 |
| 312 | Ontario | Toronto | York | Texas | Dallas | Oak Cliff Area | 0.0 |
| 23 | Ontario | Toronto | Central Toronto | Texas | Dallas | Oak Lawn | 0.0 |
| 52 | Ontario | Toronto | Downtown Toronto | Texas | Dallas | Oak Lawn | 0.0 |
| 81 | Ontario | Toronto | East Toronto | Texas | Dallas | Oak Lawn | 0.0 |
| 110 | Ontario | Toronto | East York | Texas | Dallas | Oak Lawn | 0.0 |
| 168 | Ontario | Toronto | Mississauga | Texas | Dallas | Oak Lawn | 0.0 |
| 226 | Ontario | Toronto | Queen's Park | Texas | Dallas | Oak Lawn | 0.0 |
| 255 | Ontario | Toronto | Scarborough | Texas | Dallas | Oak Lawn | 0.0 |
| 284 | Ontario | Toronto | West Toronto | Texas | Dallas | Oak Lawn | 0.0 |
| 313 | Ontario | Toronto | York | Texas | Dallas | Oak Lawn | 0.0 |
| 26 | Ontario | Toronto | Central Toronto | Texas | Dallas | South Central Dallas | 0.0 |
| 55 | Ontario | Toronto | Downtown Toronto | Texas | Dallas | South Central Dallas | 0.0 |
| 84 | Ontario | Toronto | East Toronto | Texas | Dallas | South Central Dallas | 0.0 |
| 113 | Ontario | Toronto | East York | Texas | Dallas | South Central Dallas | 0.0 |
| 171 | Ontario | Toronto | Mississauga | Texas | Dallas | South Central Dallas | 0.0 |
| 229 | Ontario | Toronto | Queen's Park | Texas | Dallas | South Central Dallas | 0.0 |
| 258 | Ontario | Toronto | Scarborough | Texas | Dallas | South Central Dallas | 0.0 |
| 287 | Ontario | Toronto | West Toronto | Texas | Dallas | South Central Dallas | 0.0 |
| 316 | Ontario | Toronto | York | Texas | Dallas | South Central Dallas | 0.0 |
Let us compare similarity of city's neighborhoods.
Our analysis show that the most similar city to Toronto, where the employee lives, is Chicago. We will advice to the employee to choose that city to relocate.
Of course, our analysis does not include the employee's preferences and habits. Some venues may not be attractive to the employee and by removing them we may get different results.
Note, that Forsquare provides living data, which is updated together with analyzed cities and peoples preferences, so the results are just snapshot taken at the moment. Anyway it will be interesting how the cities will look like in the future.
Purpose of this project was to give the employee imagination about three different cities to leave, one of them musts be chosen by the employee for future place to leave.
Final decision, which the employee musts take will base on similarity of cities, which will be provided to the employee by the employer. Additionally, the employee will receive lists of similar boroughs and neighborhoods, what helps him to orientate in the chosen city.